"... We describe an approach to the automatic creation of a sense tagged corpus intended to train a word sense disambiguation (WSD) system for English-Portuguese machine translation. The approach uses parallel corpora, translation dictionaries and a set of straightforward heuristics. In an evaluati ..."

We describe an approach to the automatic creation of a sense tagged corpus intended to train a word sense disambiguation (WSD) system for English-Portuguese machine translation. The approach uses parallel corpora, translation dictionaries and a set of straightforward heuristics. In an evaluation with nine corpora containing 10 ambiguous verbs, the approach achieved an average precision of 94%, compared with 58% when a state of the art statistical alignment tool was used. The resulting corpus consists of 113,802 instances tagged with the senses (i.e., translations) of the 10 verbs. Besides the word-sense tags, this corpus provides other useful information, such as POS-tags, and can be readily used as input to supervised machine learning algorithms in order to build WSD models for machine translation.

"... Although it is generally agreed that Word Sense Disambiguation (WSD) is an application dependent task, the great majority of the efforts has aimed at the development of WSD systems without considering their application. We argue that this strategy is not appropriate, since some aspects, such as the ..."

Although it is generally agreed that Word Sense Disambiguation (WSD) is an application dependent task, the great majority of the efforts has aimed at the development of WSD systems without considering their application. We argue that this strategy is not appropriate, since some aspects, such as the sense repository and the disambiguation process itself, vary according to the application. Taking Machine Translation (MT) as application and focusing on the sense repository, we present evidence for this argument by examining WSD in English-Portuguese MT of eight sample verbs. By showing that the traditional monolingual WSD strategies are not suitable for multilingual applications, we intend to motivate the development of WSD methods for particular applications. 1

by
Ambiguous Verbs In, Lucia Specia
- In Proceedings of the 17th European Summer School in Logic, Language and Information, ESSLLI-2005, 2005

"... Word sense disambiguation (WSD) is one of the most challenging outstanding problems in the current machine translation systems. An effective proposal in this context will rely on the use relevant knowledge sources. Moreover, it must perform better than the current traditional approaches. We prese ..."

Word sense disambiguation (WSD) is one of the most challenging outstanding problems in the current machine translation systems. An effective proposal in this context will rely on the use relevant knowledge sources. Moreover, it must perform better than the current traditional approaches. We present some experiments with machine learning algorithms traditionally applied to WSD, aiming to discover both the best knowledge sources and the performance of these approaches. The results confirmed those already reported in monolingual WSD, indicating collocations and semantic word associations as the best word sense distinctive characteristics. In future work, we will use the best knowledge sources discovered, along with good rules produced by a symbolic algorithm, in a new WSD approach.